2015
DOI: 10.1007/978-3-319-20553-3_4
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The Constitutive Relation Error Method: A General Verification Tool

Abstract: This chapter reviews the Constitutive Relation Error method as a general verification tool which is very suitable to compute strict and effective error bounds for linear and more generally convex Structural Mechanics problems. The review is focused on the basic features of the method and the most recent developments.

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Cited by 10 publications
(10 citation statements)
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“…being the traditional energy norms. Further information about posteriori error estimation for contact problems can be found in [62,63,64] Appendix B Quadratic second-order cone programming…”
Section: Discussionmentioning
confidence: 99%
“…being the traditional energy norms. Further information about posteriori error estimation for contact problems can be found in [62,63,64] Appendix B Quadratic second-order cone programming…”
Section: Discussionmentioning
confidence: 99%
“…The idea behind this enrichment is to improve the ellipticity properties of the cost function by adding a term which relaxes unreliable parts of the model. Introduced in the 1980s for the purpose of FE verification (and extensively developed in [26][27][28][29][30][31][32] among many other references), the CRE concept was later adapted for model validation [33][34][35][36][37] in structural dynamics to define a modified CRE (mCRE) residual to be minimized with respect to the set of updated parameters. The mCRE functional reads:…”
Section: The Modified Constitutive Relation Error (Mcre)mentioning
confidence: 99%
“…The CRE concept, explained in full detail in the works of Ladevèze and Pelle and Ladevèze and Chamoin, has similitude with various methods in the literature, such as equilibrated residual or flux‐free approaches. They all share the idea of constructing a fully equilibrated flux field, which is actually the only way to recover guaranteed and computable (no unknown constant) estimates on the discretization error.…”
Section: Error Estimation and Adaptive Processmentioning
confidence: 99%
“…It is then possible to obtain a strict computable bounding on the error scriptEQfalse(boldpfalse). It reads as follows: false|scriptEQfalse(boldpfalse)Qcorrfalse(boldpfalse)false|12ECRE()umhfalse(·,boldpfalse),trueboldq^boldp.1.5ptECRE()ũmhfalse(·,boldpfalse),truetrueboldq˜^boldp, where Q corr ( p ) is a fully computable correction term. Consequently, a computable bounding on the exact value Q ( u p ) of the quantity of interest can be defined, under the form Qfalse(boldpfalse)Qfalse(uboldpfalse)Q+false(boldpfalse) with rightQ(p)left=Qumh(·,p)+Qcorr(p)12ECREumh(·,p),q^p.ECREũmh(·,p),…”
Section: Error Estimation and Adaptive Processmentioning
confidence: 99%
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